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Conflict of Interest: In relation to this article, we declare that there is no conflict of interest.

Publication history: Received May 13, 2012
Accepted October 2, 2012

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Response surface methodology approach to optimize coagulation-flocculation process using composite coagulants

Tiroyaone Tshukudu Huaili Zheng^† Xuebin Hua Jun Yang Mingzhuo Tan¹ Jiangya Ma Yongjun Sun Guocheng Zhu

Key Laboratory of the Three Gorges Reservoir Regions Eco-Environment, Ministry of Education, Chongqing University, Chongqing 400045, China ¹Jiangmen Wealth Water Purifying Agent Co., Ltd., Jiangmen City, Guangdong 529000, China

zhl@cqu.edu.cn, ZHL6512@126.com

Korean Journal of Chemical Engineering, March 2013, 30(3), 649-657(9), 10.1007/s11814-012-0169-y

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Abstract

Response surface method and experimental design were applied as alternatives to the conventional methods for optimization of the coagulation test. A central composite design was used to build models for predicting and optimizing the coagulation process. The model equations were derived using the least square method of the Minitab 16 software. In these equations, the removal efficiency of turbidity and COD were expressed as second-order functions of the coagulant dosage and coagulation pH. By applying RSM, the optimum condition using PFPD1 was coagulant dosage of 384 mg/L and coagulation pH of 7.75. The optimum condition using PFPD2 was coagulant dosage of 390 mg/L and coagulation pH of 7.48. Confirmation experiment demonstrated a good agreement between experimental values and model predicted. This demonstrates that RSM and CCD can be successfully applied for modeling and optimizing the coagulation process using PFPD1 and PFPD2.

Keywords

Analysis of Variance (ANOVA) Optimizing Central Composite Design (CCD) Turbidity Removal COD Removal

References

Jiang JQ, Graham NJD, Water Res., 32, 930 (1998)
Zouboulis AI, Moussas PA, Desalination, 224(1-3), 307 (2008)
Zhao HZ, Luan ZK, Gao BY, Yue QY, J. Appl. Polym. Sci., 84(2), 335 (2002)
Wang Y, Gao BY, Yue QY, Wei JC, Li Q, Chem. Eng. J., 142(2), 175 (2008)
Trinh TK, Kang LS, Environ. Eng. Res., 15, 63 (2010)
Trinh TK, Kang LS, Chem. Eng. Res. Des., 89(7A), 1126 (2011)
Montgomery DC, Design and analysis of experiments, 5th Ed., John Wiley & Sons, New York (2001)
Xu CP, Kim SW, Hwang HJ, Choi JW, Yun JW, Process Biochem., 38, 1025 (2003)
Ahmad AL, Wong SS, Teng TT, Zuhairi A, J. Hazard. Mater., 145(1-2), 162 (2007)
Wang JP, Chen YZ, Ge XW, Yu HQ, Colloid Surface A., 302, 204 (2007)
Omar FM, Rahman NNNA, Ahmad A, Water, Air, Soil Pollut., 195, 345 (2008)
Amuda OS, Amoo IA, J. Hazard. Mater., 141(3), 778 (2007)
Chowdhury S, Chakraborty S, Saha PD, Environ. Sci. Pollut.Res., DOI: 10.1007/s11356-012-0989-7 (2012)
Saha PD, Chowdhury S, Das S, Arch. Environ. Sci., 6, 57 (2012)
Zhu G, Zheng HL, Zhang Z, Tshukudu T, Zhang P, Xiang X, Chem. Eng. J., 178, 50 (2011)
Gao BY, Wang Y, Yue QY, Wei JC, Li Q, Sep. Purif. Technol., 62(3), 544 (2008)
Zeng Y, Park J, Colloid Surface A., 334, 147 (2009)
Zheng HL, Zhu GC, Jiang SJ, Tshukudu T, Xiang XY, Zhang P, He QA, Desalination, 269(1-3), 148 (2011)
Jaikumar V, Ramamurthi V, J. Modern Appl. Sci., 3(4), 71 (2009)
Ghafari S, Aziz HA, Isa MH, Zinatizadeh AA, J. Hazard. Mater., 163(2-3), 650 (2009)
Wei JC, Gao BY, Yue QY, Wang Y, Lu L, J. Hazard. Mater., 165(1-3), 789 (2009)